Closed-world databases and circumscription
Artificial Intelligence
Foundations of deductive databases and logic programming
From Logic to Logic Programming
From Logic to Logic Programming
A General Theory of Deduction, Induction, and Learning
DS '01 Proceedings of the 4th International Conference on Discovery Science
Learning, Logic, and Topology in a Common Framework
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
Unifying logic, topology and learning in parametric logic
Theoretical Computer Science - Algorithmic learning theory(ALT 2002)
Inductive logic programming: yet another application of logic
INAP'05 Proceedings of the 16th international conference on Applications of Declarative Programming and Knowledge Management
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Deduction and induction are unified on the basis of a generalized notion of logical consequence, having classical first-order logic as a particular case. RichProlog is a natural extension of Prolog rooted in this generalized logic, in the same way as Prolog is rooted in classical logic. Prolog can answer 驴1 queries as a side effect of a deductive inference. RichProlog can answer 驴1 queries, 驴1 queries (as a side effect of an inductive inference), and 驴2 queries (as a side effect of an inductive inference followed by a deductive inference). RichProlog can be used to learn: a learning problem is expressed as a usual logic program, supplemented with data, and solved by asking a 驴2 query. The output is correct in the limit, i.e., when sufficient data have been provided.